ANALYSIS OF UBER PICKUPS IN NEW YORK CITY USING K-MEANS CLUSTERING ALGORITHM

  • Abhishek Upadhyay et al.

Abstract

In this paper, I worked on the Uber dataset, which contains data produced by Uber for the New York City. Uber Technologies is a P2P network for sharing platform. Uber platform links you to drivers who can take you to your destination or location. The dataset includes primary data on Uber pick-ups with details including the date, time of the ride as well as longitude-latitude information. New York City has five districts, Brooklyn, Queens, Manhattan, Bronx, and Staten Island. I will use k-means clustering on the set of data to make it easier to navigate the set of data and classify the various parts of the New York City. This data, when extracted over location that can provide details on the main attractions of the city, it can help us to understand the specific areas of the city, such as residential areas, offices, school zones, highways, etc.

Published
2019-12-08